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Sanclemente JL, Rivera-Velez SM, Horohov DW, Dasgupta N, Sanz MG. Plasma metabolome of healthy and Rhodococcus equi-infected foals over time. Equine Vet J 2023; 55:831-842. [PMID: 36273247 DOI: 10.1111/evj.13894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 09/25/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Foals that develop pulmonary ultrasonographic lesions on Rhodococcus equi (R. equi) endemic farms are treated with antibiotics because those at risk of developing clinical pneumonia (~20%) cannot be recognised early. Candidate biomarkers identified using metabolomics may aid targeted treatment strategies against R. equi. OBJECTIVES (1) To describe how foal ageing affects their plasma metabolome (birth to 8 weeks) and (2) to establish the effects that experimental infection with Rhodococcus equi (R. equi) has on foal metabolome. STUDY DESIGN Experimental study. METHODS Nine healthy newborn foals were experimentally infected with R. equi as described in a previous study. Foals were treated with oral antibiotics if they developed clinical pneumonia (n = 4, clinical group) or remained untreated if they showed no signs of disease (n = 5, subclinical group). A group of unchallenged foals (n = 4) was also included in the study. By the end of the study period (8 weeks), all foals were free of disease. This status was confirmed with transtracheal wash fluid evaluation and culture as well as thoracic ultrasonography. Plasma metabolomics was determined by GC-MS weekly for the study duration (8 weeks). RESULTS Foals' plasma metabolome was altered by ageing (birth to 8 weeks) and experimental infection with R. equi as demonstrated using multivariate statistical analysis. The intensities of 25 and 28 metabolites were altered by ageing and infection (p < 0.05) respectively. Furthermore, 20 metabolites changed by more than 2-fold between clinical and subclinical groups. MAIN LIMITATIONS The number of foals is limited. Foals were experimentally infected with R. equi. CONCLUSIONS Ageing and R. equi infection induced changes in the plasma metabolome of foals. These results provide an initial description of foal's plasma metabolome and serve as background for future identification of R. equi pneumonia biomarkers.
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Affiliation(s)
- Jorge L Sanclemente
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA
| | - Sol M Rivera-Velez
- Molecular Determinants Core, Johns Hopkins All Children's Hospital, St Petersburg, Florida, USA
| | - David W Horohov
- Maxwell H. Gluck Equine Research Center, Department of Veterinary Clinical Sciences, University of Kentucky, Lexington, Kentucky, USA
| | - Nairanjana Dasgupta
- Department of Mathematics and Statistics, College of Arts and Sciences, Washington State University, Pullman, Washington, USA
| | - Macarena G Sanz
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA
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Lemas DJ, Du X, Dado-Senn B, Xu K, Dobrowolski A, Magalhães M, Aristizabal-Henao JJ, Young BE, Francois M, Thompson LA, Parker LA, Neu J, Laporta J, Misra BB, Wane I, Samaan S, Garrett TJ. Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal. Nutrients 2023; 15:3768. [PMID: 37686800 PMCID: PMC10490210 DOI: 10.3390/nu15173768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/20/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023] Open
Abstract
Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography-high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe-host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.
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Affiliation(s)
- Dominick J. Lemas
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
- Department of Obstetrics and Gynecology, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
- Center for Perinatal Outcomes Research, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | - Xinsong Du
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Bethany Dado-Senn
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Ke Xu
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Amanda Dobrowolski
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Marina Magalhães
- Department of Behavioral Nursing Science, College of Nursing, University of Florida, Gainesville, FL 32603, USA;
| | - Juan J. Aristizabal-Henao
- Department of Physiological Science, Center for Environmental and Human Toxicology, College of Veterinary Science, University of Florida, Gainesville, FL 32608, USA;
| | - Bridget E. Young
- Division of Breastfeeding and Lactation Medicine, University of Rochester Medical Center, Rochester, NY 14642, USA;
| | - Magda Francois
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Lindsay A. Thompson
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Leslie A. Parker
- Center for Perinatal Outcomes Research, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | - Josef Neu
- Department of Pediatrics, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | - Jimena Laporta
- Department of Obstetrics and Gynecology, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | | | - Ismael Wane
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Samih Samaan
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Timothy J. Garrett
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
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Gu W, Zhang L, Han T, Huang H, Chen J. Dynamic Changes in Gut Microbiome of Ulcerative Colitis: Initial Study from Animal Model. J Inflamm Res 2022; 15:2631-2647. [PMID: 35494313 PMCID: PMC9049869 DOI: 10.2147/jir.s358807] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 04/13/2022] [Indexed: 12/23/2022] Open
Abstract
Background An animal model of DSS-induced UC has been widely used in basic research, and the dysbiosis of gut microbiome is one of the important pathogenetic mechanisms of DSS-induced UC, but its dynamic changes and correlation with inflammatory factors are not clear yet. Methods Clinical signs and tissue damage degree of C57BL/6 ulcerative colitis mice model induced by different concentrations of DSS were compared with that of normal mice, and finally the optimal concentration of DSS was determined. Then we analyzed the sequencing results of gut microbiome and inflammatory factors to determine the dynamic patterns of gut microbiome and their correlation with the inflammatory factors. Results DSS at 2.5% and 3.0% concentration could cause intestinal injury and induce colitis. However, 3.0% DSS resulted in higher mortality. In addition, there were dynamic changes of gut microbiome in DSS-induced UC model: the relative abundance of intestinal flora increased first and then decreased in Bacteroides, Parabacteroides, Romboutsia, Clostridium_sensu_stricto_1, Lachnospiraceae_NK4A136_group, norank_f_norank_o_Clostridia_UCG-014, Parasutterella, and decreased first and then increased in Lactobacillus, Muribaculum, norank_f_Muribaculaceae, in addition, Bifidobacterium, Coriobacteriaceae_UCG-002 and Enterorhabdus did not change in the first 14 days but increased significantly on day 21. Moreover, inflammatory cytokines were closely associated with the imbalance of the intestinal microbiota in mice with UC: most pathogenic bacteria in the intestinal tract of the UC animal model were positively correlated with pro-inflammatory factors and negatively correlated with anti-inflammatory factors, while beneficial bacteria were the opposite. Conclusion Intestinal microecology plays an important role in DSS-induced UC model, and the relative abundance of gut microbiome changes dynamically in the occurrence and development of ulcerative colitis.
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Affiliation(s)
- Wenchao Gu
- Department of Traditional Chinese Medicine, Central Hospital Affiliated to ShanDong First Medical University (Jinan Central Hospital), Jinan, 250000, People’s Republic of China
| | - Liangkun Zhang
- Department of Traditional Chinese Medicine, Central Hospital Affiliated to ShanDong First Medical University (Jinan Central Hospital), Jinan, 250000, People’s Republic of China
| | - Tao Han
- Shandong University of Traditional Chinese Medicine, Jinan, 250355, People’s Republic of China
| | - Hailiang Huang
- Shandong University of Traditional Chinese Medicine, Jinan, 250355, People’s Republic of China
- Hailiang Huang, Shandong University of Traditional Chinese Medicine, No. 4655 Daxue Road, Changqing District, Jinan, People’s Republic of China, Tel +86 15628987355, Email
| | - Jian Chen
- Department of Traditional Chinese Medicine, Central Hospital Affiliated to ShanDong First Medical University (Jinan Central Hospital), Jinan, 250000, People’s Republic of China
- Correspondence: Jian Chen, Central Hospital Affiliated to ShanDong First Medical University (Jinan Central Hospital), No. 105 Jiefang Road, Lixia District, Jinan, People’s Republic of China, Tel +86 133 7058 7597, Email
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